Performance Assessment of Atmospheric Correction for Multispectral Data of GF-4 on Inland Case Ⅱ Turbid Water
SONG Ting1, 2, GONG Shao-qi3, LIU Jun-zhi4, 5*, GU Zheng-fan2, SHI Jun-zhe2, WU Wei2
1. School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
2. Wuxi Environmental Monitoring Centre, Wuxi 214121, China
3. School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China
4. Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
5. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Abstract：GF-4 satellite is the first geostationary satellite with high spatial resolution in China, which has great potential in the aspects of inland water monitoring. This paper takes the Taihu Lake as study area to evaluate the accuracy of GF-4 derived spectral reflectance after atmospheric correction, aiming to provide valuable information for the application of GF-4 data to water color remote sensing. The MODIS-aided improved Gordon atmospheric correction algorithm was used to conduct atmospheric correction for GF-4 images obtained on 2016-07-21 and 2016-08-17. In situ measurements of quasi-synchronous samples and atmospheric corrected GOCI (Geostationary Ocean Color Imager) data were used to validate the GF-4 derived spectral reflectance. The results show that the red-light B4 band had the highest accuracy with RMSE (Root Mean Square Error) of 1.25×10-3 and MAPE (Mean Absolute Percentage Error) of 10.71%, the green-light B3 band had RMSE of 2.43×10-3 and MAPE of 13.21%, and the near-infrared B5 band had RMSE of 1.95×10-3 and MAPE of 33.06%. The blue-light B2 band had the worst accuracy with RMSE of 6.81×10-3 and MAPE of 53.55%. The accuracy of B3, B4 and B5 bands of GF-4 were higher than those of GOCI. This is because that the spatial resolution of GF-4 is much higher than that of GOCI, so the errors caused by mixed pixel were relatively smaller, showing the advantage of GF-4 as a high-resolution geostationary satellite when used in water color remote sensing. The accuracy of B2 band of GF-4 was lower than that of GOCI, indicating the B2 band of GF-4 still has room for improvement. In the future, the B2 band should be corrected separately, and the usage of this band in water color remote sensing should be avoided if it is not corrected properly. Overall, the multispectral data of GF-4 has relatively high accuracy and can used to monitor the inland case II turbidwater. In order to improve the accuracy of GF-4 derived spectral reflectance, several researches should be conducted in the future. First, aerosol observation stations should be established to obtained long-term data needed by the multiple scattering algorithm forlocalaerosol. Second, the study area should be divided into several sub-regions in order to reduce the errors caused by the assumption that the air condition was the same for the whole study area. The third, the spatial resolution of GF-4 was 50 m, while the effective area of thespectrograph probe was only 1 m2. Spectrum data should be collected at multiple points within one GF-4 pixel, so that the errors caused by scale mismatch can be reduced.
Key words：GF-4 satellite; Atmospheric correction; GOCI; Taihu Lake
宋 挺，龚绍琦，刘军志，顾征帆，石浚哲，吴 蔚. 浑浊二类水体的高分四号卫星大气校正效果分析[J]. 光谱学与光谱分析, 2018, 38(04): 1191-1197.
SONG Ting, GONG Shao-qi, LIU Jun-zhi, GU Zheng-fan, SHI Jun-zhe, WU Wei. Performance Assessment of Atmospheric Correction for Multispectral Data of GF-4 on Inland Case Ⅱ Turbid Water. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1191-1197.
[1] WANG Zhong-ting, ZHANG Xu-huan, YUAN Shu-yun, et al(王中挺, 张玉环, 袁淑云, 等). Environment and Sustainable Development(环境与可持续发展), 2016, 5: 113.
[2] FAN Yi-da, WU Wei(范一大, 吴 玮). Disaster Reduction in China(中国减灾), 2016, 2: 48.
[3] Huot J P, Tait H, Rast M, et al. ESA Bulletin, 2001, 106: 58.
[4] Gordon H R, Wang Menghua. Applied Optics, 1994, 33(3): 443.
[5] ZHOU Li, LI Yun-mei, GUO Yu-long, et al(周 莉，李云梅，郭宇龙，等). Acta Optica Sinica(光学学报)，2014，34(2)：020102.
[6] CHEN Lei, DENG Ru-ru, HE Ying-qing, et al(陈 蕾，邓孺孺，何颖清，等). Acta Oceanological Sinica(海洋学报)，2012，34(5)：183.
[7] XIAO Yan-fang, ZHAO Wen-ji, ZHU Lin(肖艳芳，赵文吉，朱 琳). Marine Sciences(海洋科学)，2012，36(8)：59.
[8] LI Jun-sheng, ZHANG Bing, CHEN Zheng-chao, et al(李俊生, 张 兵, 陈正超, 等). Science in China(E)(中国科学E辑), 2006, 36(S1): 141.
[9] TAN Jing, LI Yun-mei, ZHAO Yun-lin, et al(檀 静, 李云梅, 赵运林, 等). Journal of Remote Sensing(遥感学报), 2013, 17(4)：780.
[10] JIN Xin, LI Yun-mei, WANG Qiao, et al(金 鑫, 李云梅, 王 桥, 等). Journal of Lake Science(湖泊科学), 2010, 22(4): 504.
[11] TANG Jun-wu, TIAN Guo-liang, WANG Xiao-yong, et al(唐军武, 田国良, 汪小勇, 等). Journal of Remote Sensing(遥感学报), 2004, 8(1)：38.
[12] BAO Ying, TIAN Qing-jiu, CHEN Hao, et al(包 颖, 田庆久, 陈 昊, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(8): 2562.
[13] TANG Jun-wu, MA Chao-fei, NIU Sheng-li, et al(唐军武, 马超飞，牛生丽，等). Science in China(E)(中国科学E辑), 2005, 35(S1): 156.
[14] Wang M H, Fran B A. IEEE Trans. Geosci. Remote Sen., 2000, 38(1): 184.
[15] Wang M, Gordon H R. Remote Sensing of Environment, 1994, 50(3): 231.
[16] Gould R W, Arnone R A, Martinolich P M. Appl. Opt., 1999, 38(12): 2377.
[17] Yacobi Y Z, Gitelson A, Mayo A. Journal of Plankton Research, 1995, 17：2155.
